Antenna Season Report Notebook¶

Josh Dillon, Last Revised January 2022

This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.

In [1]:
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
In [2]:
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
In [3]:
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "167"
csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
In [4]:
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))

Antenna 167 Report

In [5]:
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
In [6]:
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 30 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_
Found 28 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
In [7]:
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'

Load relevant info from summary CSVs¶

In [8]:
this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
            antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
        else:
            antnum = int(row['Ant'])
        if antnum != int(antenna):
            continue
        
        if np.issubdtype(type(row['Node']), np.integer):
            row['Node'] = str(row['Node'])
        if type(row['Node']) == str and row['Node'].isnumeric():
            row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break
In [9]:
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])

Table 1: Per-Night RTP Summary Info For This Atenna¶

This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.

In [10]:
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))

Antenna 167, Node N15:

Out[10]:
JDs A Priori Status Auto Metrics Flags Dead Fraction in Ant Metrics (Jee) Dead Fraction in Ant Metrics (Jnn) Crossed Fraction in Ant Metrics Flag Fraction Before Redcal Flagged By Redcal chi^2 Fraction ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score Average Dead Ant Metric (Jee) Average Dead Ant Metric (Jnn) Average Crossed Ant Metric Median chi^2 Per Antenna (Jee) Median chi^2 Per Antenna (Jnn)
2459846 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 62.305189 48.607562 4.669849 3.323381 12.424158 8.814488 26.846160 24.781759 0.6769 0.5992 0.3448 3.201487 3.698195
2459845 digital_ok 100.00% 7.74% 2.21% 0.00% 100.00% 0.00% 71.863648 66.766401 9.527705 7.357551 17.869823 11.679544 80.898419 78.590893 0.5730 0.6123 0.1799 3.358195 3.840393
2459844 digital_ok 100.00% 100.00% 100.00% 0.00% - - 10.687615 9.935456 4.716454 6.924323 2.937605 5.262129 1.067596 -0.926189 0.0250 0.0252 0.0005 nan nan
2459842 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 13.143802 13.735565 -1.544976 -1.517802 5.303055 -0.154139 14.656773 3.766201 0.5988 0.5748 0.0843 5.633222 5.111579
2459841 digital_ok 100.00% 0.00% 0.00% 0.00% - - 16.629607 13.247788 101.387926 111.600134 243.825115 190.080865 332.339105 222.129269 0.5791 0.5938 0.1685 nan nan
2459839 digital_ok 100.00% - - - - - -0.057086 2.010251 -0.391359 -0.501826 2.525912 6.366520 6.287415 3.988518 nan nan nan nan nan
2459838 digital_ok 100.00% 7.97% 0.00% 0.00% 100.00% 0.00% 41.929915 20.861332 18.100304 20.249612 20.329930 20.322800 3.218266 3.246733 0.5467 0.5563 0.2348 0.000000 0.000000
2459836 digital_ok - 0.54% 0.00% 0.00% - - nan nan nan nan nan nan nan nan 0.5884 0.5402 0.2858 nan nan
2459835 digital_ok 100.00% 0.00% 0.00% 0.00% - - 4.023747 4.352303 11.684606 11.917262 29.334704 21.007882 13.011978 12.178071 0.6724 0.5091 0.3833 nan nan
2459833 digital_ok 100.00% 0.00% 0.00% 0.00% - - 7.792489 8.811748 49.891188 52.592197 110.135065 94.684408 5.399992 33.890966 0.6875 0.4838 0.3831 nan nan
2459832 digital_ok 100.00% 0.00% 2.69% 0.00% 100.00% 0.00% 29.137724 28.373581 15.377111 16.271672 10.387213 8.893505 1.540194 6.576261 0.6912 0.4206 0.4630 3.218520 2.882127
2459831 digital_ok 0.00% 100.00% 100.00% 0.00% - - -0.427433 1.342358 -0.432165 -0.566046 1.497267 1.703116 3.979541 2.248315 0.0331 0.0300 0.0028 nan nan
2459830 digital_ok 100.00% 0.00% 13.44% 0.00% 100.00% 0.00% 48.620293 27.119495 17.970409 21.427242 29.676966 28.376971 13.075871 8.227094 0.6420 0.4150 0.4116 4.277395 3.233029
2459829 digital_ok 100.00% 6.98% 4.83% 0.00% 100.00% 0.00% 39.917092 34.851708 20.498451 21.522425 25.979905 23.518532 20.898287 14.388688 0.5699 0.5052 0.2306 2.131586 1.862610
2459828 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 15.963278 21.991358 15.805777 15.868155 27.306635 25.058034 13.616681 26.897860 0.6940 0.4290 0.3908 4.383455 2.647757
2459827 digital_ok 100.00% 8.06% 0.00% 0.00% 100.00% 0.00% 51.593268 22.482244 23.234680 27.247702 20.835633 19.292382 97.109792 38.891812 0.5541 0.5484 0.2443 3.749418 3.790128
2459826 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 38.203012 19.937845 17.688660 22.100281 34.053960 35.661441 4.900779 4.293258 0.6465 0.4737 0.3347 0.000000 0.000000
2459825 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 40.314047 22.318657 13.295627 16.730786 27.723292 24.873296 33.623156 16.516081 0.6391 0.4605 0.3447 0.000000 0.000000
2459824 digital_ok 100.00% 15.03% 0.00% 0.00% 100.00% 0.00% 52.512585 21.700953 19.730310 24.288382 15.509459 19.989232 15.627162 13.862703 0.4952 0.5720 0.1732 0.000000 0.000000
2459823 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 20.958396 20.652667 15.205119 19.109062 26.948613 30.173406 37.409301 21.875303 0.6109 0.5061 0.3478 0.000000 0.000000
2459822 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 37.050258 18.184126 15.796180 20.487084 27.040196 24.734654 58.675336 11.649535 0.6464 0.5166 0.3178 0.000000 0.000000
2459821 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 26.115748 20.851031 17.056415 19.995010 24.389869 22.174873 56.090562 18.695465 0.6434 0.4852 0.3391 5.551685 4.572145
2459820 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 36.551473 19.806752 22.513773 25.396318 57.565331 55.354413 70.575186 6.145162 0.5974 0.5596 0.2834 0.000000 0.000000
2459817 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 28.916903 20.258925 12.453685 16.419230 28.178151 28.934090 7.583537 4.854705 0.6628 0.5363 0.2870 1.003000 1.029788
2459816 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 11.654457 17.972673 23.253792 24.326709 39.038375 37.461448 2.073521 3.582126 0.7252 0.4765 0.3817 5.596781 3.462404
2459815 digital_ok 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 21.222447 20.103678 15.321920 18.922541 37.038386 38.647922 9.070658 5.889027 0.6731 0.5370 0.3491 4.120304 2.905525
2459814 digital_ok 0.00% - - - - - nan nan nan nan nan nan nan nan nan nan nan nan nan
2459813 digital_ok 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% nan nan inf inf nan nan nan nan nan nan nan 0.000000 0.000000

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

In [11]:
htmls_to_display = []
for am_html in auto_metric_htmls:
    html_to_display = ''
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line:
            htmls_to_display.append(html_to_display)
            break

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.

In [12]:
for i, html_to_display in enumerate(htmls_to_display):
    if i == 100:
        break
    display(HTML(html_to_display))

Antenna 167: 2459846

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
167 N15 digital_ok ee Shape 62.305189 62.305189 48.607562 4.669849 3.323381 12.424158 8.814488 26.846160 24.781759

Antenna 167: 2459845

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
167 N15 digital_ok ee Temporal Discontinuties 80.898419 66.766401 71.863648 7.357551 9.527705 11.679544 17.869823 78.590893 80.898419

Antenna 167: 2459844

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
167 N15 digital_ok ee Shape 10.687615 10.687615 9.935456 4.716454 6.924323 2.937605 5.262129 1.067596 -0.926189

Antenna 167: 2459842

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
167 N15 digital_ok ee Temporal Discontinuties 14.656773 13.143802 13.735565 -1.544976 -1.517802 5.303055 -0.154139 14.656773 3.766201

Antenna 167: 2459841

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
167 N15 digital_ok ee Temporal Discontinuties 332.339105 16.629607 13.247788 101.387926 111.600134 243.825115 190.080865 332.339105 222.129269

Antenna 167: 2459839

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
167 N15 digital_ok nn Temporal Variability 6.366520 2.010251 -0.057086 -0.501826 -0.391359 6.366520 2.525912 3.988518 6.287415

Antenna 167: 2459838

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
167 N15 digital_ok ee Shape 41.929915 20.861332 41.929915 20.249612 18.100304 20.322800 20.329930 3.246733 3.218266

Antenna 167: 2459835

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
167 N15 digital_ok ee Temporal Variability 29.334704 4.352303 4.023747 11.917262 11.684606 21.007882 29.334704 12.178071 13.011978

Antenna 167: 2459833

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
167 N15 digital_ok ee Temporal Variability 110.135065 8.811748 7.792489 52.592197 49.891188 94.684408 110.135065 33.890966 5.399992

Antenna 167: 2459832

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
167 N15 digital_ok ee Shape 29.137724 29.137724 28.373581 15.377111 16.271672 10.387213 8.893505 1.540194 6.576261

Antenna 167: 2459831

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
167 N15 digital_ok ee Temporal Discontinuties 3.979541 -0.427433 1.342358 -0.432165 -0.566046 1.497267 1.703116 3.979541 2.248315

Antenna 167: 2459830

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
167 N15 digital_ok ee Shape 48.620293 48.620293 27.119495 17.970409 21.427242 29.676966 28.376971 13.075871 8.227094

Antenna 167: 2459829

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
167 N15 digital_ok ee Shape 39.917092 34.851708 39.917092 21.522425 20.498451 23.518532 25.979905 14.388688 20.898287

Antenna 167: 2459828

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
167 N15 digital_ok ee Temporal Variability 27.306635 21.991358 15.963278 15.868155 15.805777 25.058034 27.306635 26.897860 13.616681

Antenna 167: 2459827

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
167 N15 digital_ok ee Temporal Discontinuties 97.109792 51.593268 22.482244 23.234680 27.247702 20.835633 19.292382 97.109792 38.891812

Antenna 167: 2459826

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
167 N15 digital_ok ee Shape 38.203012 19.937845 38.203012 22.100281 17.688660 35.661441 34.053960 4.293258 4.900779

Antenna 167: 2459825

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
167 N15 digital_ok ee Shape 40.314047 22.318657 40.314047 16.730786 13.295627 24.873296 27.723292 16.516081 33.623156

Antenna 167: 2459824

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
167 N15 digital_ok ee Shape 52.512585 52.512585 21.700953 19.730310 24.288382 15.509459 19.989232 15.627162 13.862703

Antenna 167: 2459823

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
167 N15 digital_ok ee Temporal Discontinuties 37.409301 20.652667 20.958396 19.109062 15.205119 30.173406 26.948613 21.875303 37.409301

Antenna 167: 2459822

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
167 N15 digital_ok ee Temporal Discontinuties 58.675336 37.050258 18.184126 15.796180 20.487084 27.040196 24.734654 58.675336 11.649535

Antenna 167: 2459821

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
167 N15 digital_ok ee Temporal Discontinuties 56.090562 20.851031 26.115748 19.995010 17.056415 22.174873 24.389869 18.695465 56.090562

Antenna 167: 2459820

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
167 N15 digital_ok ee Temporal Discontinuties 70.575186 36.551473 19.806752 22.513773 25.396318 57.565331 55.354413 70.575186 6.145162

Antenna 167: 2459817

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
167 N15 digital_ok nn Temporal Variability 28.934090 28.916903 20.258925 12.453685 16.419230 28.178151 28.934090 7.583537 4.854705

Antenna 167: 2459816

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
167 N15 digital_ok ee Temporal Variability 39.038375 17.972673 11.654457 24.326709 23.253792 37.461448 39.038375 3.582126 2.073521

Antenna 167: 2459815

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
167 N15 digital_ok nn Temporal Variability 38.647922 20.103678 21.222447 18.922541 15.321920 38.647922 37.038386 5.889027 9.070658

Antenna 167: 2459814

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
167 N15 digital_ok nn Shape nan nan nan nan nan nan nan nan nan

Antenna 167: 2459813

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
167 N15 digital_ok nn Shape nan nan nan inf inf nan nan nan nan
In [ ]: